Beschreibung
Produktdetails
Format
ePUB
Kopierschutz
Ja
Family Sharing
Ja
Text-to-Speech
Ja
Erscheinungsdatum
28.01.2025
Verlag
ManningSeitenzahl
432 (Printausgabe)
Dateigröße
19956 KB
Sprache
Englisch
EAN
9781638356134
Learn how generative AI works by building your very own models that can write coherent text, create realistic images, and even make lifelike music.
Learn Generative AI with PyTorch teaches the underlying mechanics of generative AI by building working AI models from scratch. Throughout, you'll use the intuitive PyTorch framework that's instantly familiar to anyone who's worked with Python data tools. Along the way, you'll master the fundamentals of General Adversarial Networks (GANs), Transformers, Large Language Models (LLMs), variational autoencoders, diffusion models, LangChain, and more!
In Learn Generative AI with PyTorch you'll build these amazing models:
About the technology
Transformers, Generative Adversarial Networks (GANs), diffusion models, LLMs, and other powerful deep learning patterns have radically changed the way we manipulate text, images, and sound. Generative AI may seem like magic at first, but with a little Python, the PyTorch framework, and some practice, you can build interesting and useful models that will train and run on your laptop. This book shows you how.
About the book
Learn Generative AI with PyTorch introduces the underlying mechanics of generative AI by helping you build your own working AI models. You'll begin by creating simple images using a GAN, and then progress to writing a language translation transformer line-by-line. As you work through the fun and fascinating projects, you'll train models to create anime images, write like Hemingway, make music like Mozart, and more. You just need Python and a few machine learning basics to get started. You'll learn the rest as you go!
What's inside
Examples use simple Python. No deep learning experience required.
About the author
Mark Liu is the founding director of the Master of Science in Finance program at the University of Kentucky.
The technical editor on this book was Emmanuel Maggiori.
Learn Generative AI with PyTorch teaches the underlying mechanics of generative AI by building working AI models from scratch. Throughout, you'll use the intuitive PyTorch framework that's instantly familiar to anyone who's worked with Python data tools. Along the way, you'll master the fundamentals of General Adversarial Networks (GANs), Transformers, Large Language Models (LLMs), variational autoencoders, diffusion models, LangChain, and more!
In Learn Generative AI with PyTorch you'll build these amazing models:
- A simple English-to-French translator
- A text-generating model as powerful as GPT-2
- A diffusion model that produces realistic flower images
- Music generators using GANs and Transformers
- An image style transfer model
- A zero-shot know-it-all agent
About the technology
Transformers, Generative Adversarial Networks (GANs), diffusion models, LLMs, and other powerful deep learning patterns have radically changed the way we manipulate text, images, and sound. Generative AI may seem like magic at first, but with a little Python, the PyTorch framework, and some practice, you can build interesting and useful models that will train and run on your laptop. This book shows you how.
About the book
Learn Generative AI with PyTorch introduces the underlying mechanics of generative AI by helping you build your own working AI models. You'll begin by creating simple images using a GAN, and then progress to writing a language translation transformer line-by-line. As you work through the fun and fascinating projects, you'll train models to create anime images, write like Hemingway, make music like Mozart, and more. You just need Python and a few machine learning basics to get started. You'll learn the rest as you go!
What's inside
- Build an English-to-French translator
- Create a text-generation LLM
- Train a diffusion model to produce high-resolution images
- Music generators using GANs and Transformers
Examples use simple Python. No deep learning experience required.
About the author
Mark Liu is the founding director of the Master of Science in Finance program at the University of Kentucky.
The technical editor on this book was Emmanuel Maggiori.
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